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Medium and long-term typical daily load curve prediction method based on functional nonparametric regression

A non-parametric regression, daily load technology, used in forecasting, data processing applications, instruments, etc., can solve problems such as large errors and rough forecast results, and achieve the effect of high forecast accuracy

Active Publication Date: 2017-04-26
WUHAN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The prediction result of this method is relatively rough and the error is large

Method used

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  • Medium and long-term typical daily load curve prediction method based on functional nonparametric regression
  • Medium and long-term typical daily load curve prediction method based on functional nonparametric regression
  • Medium and long-term typical daily load curve prediction method based on functional nonparametric regression

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Embodiment

[0049] 1. The technical solution of the present invention will be further described below with reference to the drawings and embodiments.

[0050] The present invention includes the following steps:

[0051] Step 1: Taking the maximum load value in each historical typical daily load curve as the reference value, normalize each historical typical daily load curve; proceed based on the following formula:

[0052] S * (t m )=S(t m ) / S max m=1,2,...,P,

[0053] Where S(t m ) Represents the load value at each moment of the typical daily load curve; S max Represents the maximum load value of a typical daily load curve; S * (t m ) Represents the value of each time after the normalization of the typical daily load curve, and P represents the number of time;

[0054] Step 2: Use the semi-metric calculation method based on functional principal component analysis to calculate the semi-metric between the normalized historical curve samples, and use the cross-validation method to calculate the opti...

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Abstract

The invention discloses a medium-and-long term typical daily load curve prediction method based on function type nonparametric regression which comprises the following steps: according to an existing historical daily load curve, based on a functional data analysis theory and a nonparametric kernel density estimation method, establishing a functional nonparametric regression prediction model; and by considering a daily load factor and a minimum load factor of a typical day to be predicted, establishing a quadratic programming model to correct a prediction curve of the functional nonparametric regression prediction model, and finally, obtaining the prediction curve meeting a load characteristic index requirement of the typical day to be predicted. A simulation example based on typical daily load data of a certain provincial power grid in China and PJM (Pennsylvania-New Jersey-Maryland) electric power company in America proves that the method disclosed by the invention is simple and practical, and is accurate in prediction result. The method has a god popularization value and application prospect.

Description

Technical field [0001] The invention belongs to the field of power system load forecasting, and relates to a medium and long-term typical daily load curve forecasting method based on a functional non-parametric regression model. Background technique [0002] Medium- and long-term typical daily load curve forecasting refers to the forecasting of typical daily load time series curves for months, seasons, and years from 1 to 10 years. It is of great significance for power supply and grid optimization. It is the system's power distribution, review of peak shaving capabilities, and evaluation The basis for the benefit of peak shift adjustment of interconnected systems. [0003] Different from the short-term daily load curve forecasting, the medium and long-term typical daily load curve forecasting has the following characteristics: the typical daily load curves of the same month in different years are similar in shape and have similar changes; typical daily load characteristic indicator...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06Q50/06
CPCY04S10/50
Inventor 徐箭许梁孙涛黄磊
Owner WUHAN UNIV
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